Learning normal appearance for fetal anomaly screening: Application to the unsupervised detection of Hypoplastic Left Heart Syndrome

no code implementations • 15 Nov 2020 • Elisa Chotzoglou, Thomas Day, Jeremy Tan, Jacqueline Matthew, David Lloyd, Reza Razavi, John Simpson, Bernhard Kainz

Congenital heart disease is considered as one the most common groups of congenital malformations which affects $6-11$ per $1000$ newborns.

Anatomy Anomaly Detection

Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening

no code implementations • 16 Aug 2020 • Jeremy Tan, Anselm Au, Qingjie Meng, Sandy FinesilverSmith, John Simpson, Daniel Rueckert, Reza Razavi, Thomas Day, David Lloyd, Bernhard Kainz

In this paper we discuss the potential for deep learning techniques to aid in the detection of congenital heart disease (CHD) in fetal ultrasound.

Classification General Classification

Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers

no code implementations • 7 Aug 2019 • Samuel Budd, Matthew Sinclair, Bishesh Khanal, Jacqueline Matthew, David Lloyd, Alberto Gomez, Nicolas Toussaint, Emma Robinson, Bernhard Kainz

Manual estimation of fetal Head Circumference (HC) from Ultrasound (US) is a key biometric for monitoring the healthy development of fetuses.

Probabilistic Deep Learning